clustering

The family Verbenaceae, currently consists of Verbena and Phyla genera in different parts of Iran, especially northern provinces. The frame of this family has undergone significant changes in comparison with the previous references. For example, Vitex and Clerodendrum have been defined as the genera of this family in previous references. Accordingly, in this study, the relationship among these four genera has been evaluated using morphological and leaf anatomical characters of 20 samples. For this purpose, 67 qualitative and quantitative morphological and anatomical traits were used. The analysis of data was performed using R software ver. 4.3.1. For simultaneous analysis of quantitative and qualitative data, Factor Analysis of Mixed Data (FAMD) method was applied. The results of this study indicate the high value of some quantitative traits such as main vein xylem length, seed width, style length and blade width and some qualitative traits such as blade epidermal cells shape, stomata position, two arms of blade position in relation to each other, indumentum type, main vein epidermal cells shape, petal color, blade vascular bundles number, density of indumentum, leaf margin shape and stem branches length in the clustering of the genera. Totally, Analysis of data led to the separation of these genera. In accordance with the phylogenetic studies, Vitex and Clerodendrum show more affinity to each other and are separated from the currently native members of Verbenaceae in Iran, i.e. Verbena and Phyla.

Plant community’s classification provides an organization framework for design of future studies of the Functional features of communities or systems and the relationship between species and the environment of the studied region and since the plant species growing in an area are affected by environmental and biological factors on these regions, Therefore, identification and classification of vegetation distribution and climatic, soil and geomorphometry properties are necessary. In this research, vegetation Sampling was done by random-systematic method to place plots along four transects. In each plot, vegetation Cover information (name of plant species and percentage cover) was recorded, and at the beginning and end of each transect was digging the soil profile. Then, climatic and geomorphometry data were extracted. In order clustering regions based on climatic, soil, geomorphometry factors, was used hierarchical method and to calculate distance between clusters was used Ward's method. The results of regional clustering based on environmental factors showed that these results correspond with reality and areas with a zero percentage coverage of Artemisia sieberi in a cluster and areas with a moderate to high level of A. sieberi were found in other clusters. Generally, it can be concluded that there is a relationship between the environmental factors and the distribution pattern of the plants.

The amphipods of genus Niphargus Schiödte, 1847 inhabit in subterranean waters and constitute a substantial part of the groundwater biodiversity. In the last decades, there have been many developments for using of modelling algorithms, although not exclusive to the specific case of subterranean habitats. In this study, ecological variables were used to investigate the effect of environmental factors on Niphargus genus distribution. The occurrence points of the genus in north, west and northwest provinces were obtained from previous studies. Then, climatic variables, topography (slope, elevation, and moisture) were used, as well as temperature and moisture data at depths of 0 to 10 cm and 10 to 40 cm. In order to evaluate the similarity between habitat areas, k-mean clustering were used. Then, species distribution modeling was performed using Maximum Entropy Method at the country scale. The results showed that among all the variables used, only Bio14 had no normal distribution (P-value>0/05). Clustering results also showed that, the occurrence points of genus members is placed in two clusters, cluster 1 in the north of Iran and cluster 2 along of Zagros mountain range. There is similarities between two clusters. Two variables include the annual rainfall and soil temperature at depths of 10 to 40 cm have the most effect on the distribution of genus Niphargus. The results also showed that due to distance from the ground surface and the environmental variables, the same conditions exist in most occurrence points of this taxon.

The current morphometric research was conducted collecting Rhamnus cathartica and Rhamnus pallasii from the natural habitats in North and West of Iran. In order to clarify the relationships in studied species and understand taxonomicall values, 58 morphological characters were employed (26 quantititative and 32 qualitative characters) using numerical taxonomy, Principal Component Analysis (CPA), and cluster analysis. In this study, leaf shape, color fruit have been found to significantly contribute to the determination of the studied species (Rhamnus pallasii & Rhamnus cathartica). The results confirmed more diversity in Rh. pallasii and three sub-species. But, in Rh. Cathartica, diversity features in the two varieties were not effective. Rh. × spathulifolia were collected from sandy hill of North of Iran which was determined by morphometric features e.g., leaflet, abaxial, adaxial leaflet trichrome, and fruit color. Overall, Rh. × spathulifolia can not be considered.

A biological network represents the interaction between a set of macromolecules to drive a particular biological process. In a biological environment, abnormalities happen not only in one molecule but also through a biological network. One of the most effective methods to detect anomaly is the comparison between healthy and diseased networks. In this regard, biological network alignment is one of the most efficient ways to find the difference between healthy and diseased cells. This problem, protein-protein interaction network alignment, has been raised in two main types: Local network alignment and Global network alignment. According to the NP-completeness of this problem, different non-deterministic approaches have been proposed to tackle the Global network alignment problem. Recently, NetAl has been introduced as a common algorithm to align two networks. Although this algorithm can align two networks at the appropriate time, it does not consider biological features. In this study, we present a new framework called PRAF to improve the results of network alignment algorithms such as NetAl by considering some biological features like gene ontology (GO).